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A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
Foundation models are built by optimizing a training objective(s), which is a mathematical function that determines how model parameters are updated based on model predictions on training data. [34] Language models are often trained with a next-tokens prediction objective, which refers to the extent at which the model is able to predict the ...
A training system is a group or family of coursework that will achieve a stated series of training objectives. [1] A training system typically employs a syllabus or similar document that specifies and outlines the coursework to be followed. A training system may also incorporate a training manual that may serve as a guide, reference source, or ...
S.M.A.R.T. (or SMART) is an acronym used as a mnemonic device to establish criteria for effective goal-setting and objective development. This framework is commonly applied in various fields, including project management, employee performance management, and personal development.
Objectives and key results (OKR, alternatively OKRs) is a goal-setting framework used by individuals, teams, and organizations to define measurable goals and track their outcomes. The development of OKR is generally attributed to Andrew Grove who introduced the approach to Intel in the 1970s [ 1 ] and documented the framework in his 1983 book ...
Bloom's taxonomy is a framework for categorizing educational goals, developed by a committee of educators chaired by Benjamin Bloom in 1956. It was first introduced in the publication Taxonomy of Educational Objectives: The Classification of Educational Goals.
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